如何注释堆叠条形图并添加图例标签

Question

简而言之：

• 柱子的高度与数字不匹配。
• 标签似乎放置在错误的高度上。（应该位于每个柱子的中间）
• 在底部我还看到了“0”的标签，我真的不想在图表中看到它们。

解释：

我正在尝试制作一个堆积条形图，并在其中标记每个柱子的适当值。但由于某种原因，柱子的高度完全错误。例如，第一周绿色的柱子应该有20点长，但实际只有10点。红色的柱子应该有10点长，但只有8点左右。第17周应该有多个柱子，但实际上只有一个（白色的）。

我猜测由于错误的柱子高度，标签也被放错了位置。我不知道为什么最底部的0也显示出来了，但这也是一个问题。

我不知道这些是否都是单独的问题，应该在单独的帖子中提出，但我觉得它们都有联系，有一个解决它们所有的答案。

import matplotlib.pyplot as plt
import numpy as np


newYearWeek =[201613, 201614, 201615, 201616, 201617, 201618, 201619, 201620, 201621, 201622]
uniqueNames = ['Word1', 'Word2', 'Word3', 'Word4', 'Word5', 'Word6',
                'Word7', 'Word8', 'Word9', 'Word10', 'Word11']

#Each column in the multiarray from top to bottom represents 1 week
#Each row from left to right represents the values of that word.
#So that makes 11 rows and 10 columns.
#And yes the multidimensional array have to be like this with the 0's in it.
keywordsMuliarray = [
    [20, 3, 1, 0, 0, 1, 6, 3, 1, 2],
    [10, 1, 0, 0, 3, 1, 3, 1, 0, 2],
    [2, 2, 5, 3, 5, 4, 5, 4, 3, 2],
    [0, 4, 3, 3, 1, 0, 2, 7, 1, 2],
    [0, 0, 2, 0, 1, 1, 1, 0, 1, 3],
    [0, 0, 3, 2, 0, 0, 0, 1, 0, 0],
    [1, 0, 1, 0, 1, 0, 0, 0, 1, 1],
    [0, 0, 0, 1, 0, 1, 0, 0, 0, 0],
    [0, 1, 0, 0, 7, 6, 0, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 2, 0, 1]]

fig = plt.figure(figsize=(8.5, 5.5))
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)

N = len(newYearWeek)
ind = np.arange(N)    # the x locations for the groups
width = 0.35       # the width of the bars: can also be len(x) sequence

colors = ['seagreen', 'indianred', 'steelblue', 'darkmagenta', 'wheat',
           'orange', 'mediumslateblue', 'silver',
           'whitesmoke', 'black', 'darkkhaki', 'dodgerblue', 'crimson',
           'sage', 'navy', 'plum', 'darkviolet', 'lightpink']

def autolabel(rects, values):
    # Attach some text labels.
    for (rect, value) in zip(rects, values):
        ax.text(rect.get_x() + rect.get_width() / 2.,
                rect.get_y() + rect.get_height() / 2.,
                '%d'%value,
                ha = 'center',
                va = 'center')
left = np.zeros(len(uniqueNames)) # left alignment of data starts at zero
helpingNumber = 0
for i in range(0, len(newYearWeek)):
    rects1 = plt.bar(ind, keywordsMuliarray[helpingNumber][:],width, color=colors[helpingNumber], label=uniqueNames[helpingNumber])
    autolabel(rects1, keywordsMuliarray[helpingNumber][:])
    helpingNumber = helpingNumber+1

# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 1, box.height])

# Put a legend to the right of the current axis
ax.legend(loc='center left', fontsize=9, bbox_to_anchor=(1, 0.5))

#plt.ylabel('Scores')
plt.xticks(ind + width/2., newYearWeek, fontsize=8)
#plt.yticks(np.arange(0, 81, 10))
plt.margins(x=0.02)
plt.tight_layout(rect=[0,0,0.8,1])
plt.show()

这是当前的图表展示：

- Morganis

Answer 1

要实现您想要的功能，您需要将当前列中所有先前柱形的高度相加（列表bot_heights），如下所示：

import matplotlib.pyplot as plt
import numpy as np


newYearWeek =[201613, 201614, 201615, 201616, 201617, 201618, 201619, 201620, 201621, 201622]
uniqueNames = ['Word1', 'Word2', 'Word3', 'Word4', 'Word5', 'Word6',
                'Word7', 'Word8', 'Word9', 'Word10', 'Word11']

#Each column in the multiarray from top to bottom represents 1 week
#Each row from left to right represents the values of that word.
#So that makes 11 rows and 10 columns.
#And yes the multidimensional array have to be like this with the 0's in it.
keywordsMuliarray = [
    [20, 3, 1, 0, 0, 1, 6, 3, 1, 2],
    [10, 1, 0, 0, 3, 1, 3, 1, 0, 2],
    [2, 2, 5, 3, 5, 4, 5, 4, 3, 2],
    [0, 4, 3, 3, 1, 0, 2, 7, 1, 2],
    [0, 0, 2, 0, 1, 1, 1, 0, 1, 3],
    [0, 0, 3, 2, 0, 0, 0, 1, 0, 0],
    [1, 0, 1, 0, 1, 0, 0, 0, 1, 1],
    [0, 0, 0, 1, 0, 1, 0, 0, 0, 0],
    [0, 1, 0, 0, 7, 6, 0, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 2, 0, 1]]

fig = plt.figure(figsize=(8.5, 5.5))
ax = fig.add_subplot(111)
fig.subplots_adjust(top=0.85)

N = len(newYearWeek)
ind = np.arange(N)    # the x locations for the groups
width = 0.35       # the width of the bars: can also be len(x) sequence

colors = ['seagreen', 'indianred', 'steelblue', 'darkmagenta', 'wheat',
           'orange', 'mediumslateblue', 'silver',
           'whitesmoke', 'black', 'darkkhaki', 'dodgerblue', 'crimson',
           'sage', 'navy', 'plum', 'darkviolet', 'lightpink']

def autolabel(rects, values):
    # Attach some text labels
    for (rect, value) in zip(rects, values):
        if value > 0:
            ax.text(rect.get_x() + rect.get_width() / 2.,
             rect.get_y() + rect.get_height() / 2.,
             '%d'%value, ha = 'center', va = 'center', size = 9)

left = np.zeros(len(uniqueNames)) # left alignment of data starts at zero

# plot the first bars
rects1 = plt.bar(ind, keywordsMuliarray[0][:],width,
 color=colors[0], label=uniqueNames[0])
autolabel(rects1, keywordsMuliarray[0][:])

# put other bars on previuos
bot_heights = [0.] * len(keywordsMuliarray[0][:])
for i in xrange(1,N):
    bot_heights = [bot_heights[j] + keywordsMuliarray[i-1][j] for j in xrange(len(bot_heights))]

    rects1 = plt.bar(ind, keywordsMuliarray[i][:],width,
     color=colors[i], label=uniqueNames[i],
     bottom=bot_heights)
    autolabel(rects1, keywordsMuliarray[i][:])

# Shrink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 1, box.height])

# Put a legend to the right of the current axis
ax.legend(loc='center left', fontsize=9, bbox_to_anchor=(1, 0.5))

#plt.ylabel('Scores')
plt.xticks(ind + width/2., newYearWeek, fontsize=8)
plt.yticks(np.arange(0, 41, 5))
plt.margins(x=0.02)
plt.tight_layout(rect=[0,0,0.8,1])
plt.show()

为了防止条形图标签重叠，建议如果值为零则不添加标签（请参考修改后的autolabel函数）。结果如下图所示：

- Serenity

Answer 2

• 另一个答案没有绘制'Word11'的数据
• 数据列表和数组最容易通过加载到pandas中进行绘制
  • 使用pandas.DataFrame.plot和kind='bar'绘制数据框
  • 当从pandas绘制数据时，索引值成为轴刻度标签，列名成为分段标签
• matplotlib.pyplot.bar_label可用于添加注释
  • 有关使用.bar_label的更多选项，请参见在matplotlib柱状图上添加值标签。
• 在pandas 1.3.1、python 3.8^1.和matplotlib 3.4.2^1.中进行了测试
  1. 所需的最低版本
  • labels = [f'{v.get_height():0.0f}' if v.get_height() > 0 else '' for v in c ]没有赋值表达式(:=)

import pandas as pd
import matplotlib.pyplot as plt

# create a dataframe from the data in the OP and transpose it with .T
df = pd.DataFrame(data=keywordsMuliarray, index=uniqueNames, columns=newYearWeek).T

# display(df.head())
        Word1  Word2  Word3  Word4  Word5  Word6  Word7  Word8  Word9  Word10  Word11
201613     20     10      2      0      0      0      1      0      0       0       0
201614      3      1      2      4      0      0      0      0      1       0       0
201615      1      0      5      3      2      3      1      0      0       0       0
201616      0      0      3      3      0      2      0      1      0       0       0
201617      0      3      5      1      1      0      1      0      7       0       0

colors = ['seagreen', 'indianred', 'steelblue', 'darkmagenta', 'wheat', 'orange', 'mediumslateblue', 'silver', 'whitesmoke', 'black', 'darkkhaki']

# plot the dataframe
ax = df.plot(kind='bar', stacked=True, figsize=(9, 6), color=colors, rot=0, ec='k')

# Put a legend to the right of the current axis
ax.legend(loc='center left', fontsize=9, bbox_to_anchor=(1, 0.5))

# add annotations
for c in ax.containers:
    
    # customize the label to account for cases when there might not be a bar section
    labels = [f'{h:0.0f}' if (h := v.get_height()) > 0 else '' for v in c ]
    
    # set the bar label
    ax.bar_label(c, labels=labels, label_type='center', fontsize=8)
    
plt.show()

- Trenton McKinney